Senior DevOps Engineer · AI & Automation Specialist

Amol Jadhav

Building enterprise cloud platforms Automating complex workflows Engineering reliable CI/CD systems Turning manual process into intelligent automation Creating AI-powered DevOps solutions

Explore My Journey Download Resume

Who Am I

I simplify complexity through automation, cloud engineering, and thoughtful design.

I'm Amol — a DevOps engineer who got hooked on one idea early: software delivery should be effortless. I enjoy building CI/CD pipelines and automation that take the complexity out of building, testing and deploying applications. When the right automation is in place, releases become faster, more reliable, and teams can focus on creating great products instead of managing repetitive deployment tasks.

Over seven years I've moved from writing Python ETL jobs to running enterprise Azure DevOps platforms for insurance and banking clients — and along the way I picked up a second obsession: using AI, specifically Azure OpenAI, to remove the last mile of manual effort that automation alone can't touch, like turning a wall of pipeline logs into a release note a business stakeholder can actually read.

I like problems with a clear before-and-after: four hours of manual release work becoming ninety minutes, fifty-three dead services becoming a smaller and cheaper estate, a deployment that used to need three people becoming one self-service click. That's the kind of engineering I'm curious about, and the kind I keep coming back to.

Professional Journey

One employer, Three enterprise clients and Seven years of continuous growth.

Current

Senior DevOps Engineer

Tata Consultancy Services · Client: Ageas Insurance · Eastleigh, UK · Jan 2025 – Present

In Simple Words

I run the central automation platform that ships an insurance client's core build and release process — cutting a four-hour daily manual job down to ninety minutes, and using AI to turn technical release logs into plain-English summaries for the business.

Technical Details

Automated the complete EIS build lifecycle using Azure DevOps, Logic Apps and ADO Pipelines — reducing daily manual effort from 4 hours to 1.5 hours (~63% reduction) with hands-off pre-checks, approvals, regression validation and release note generation.
Architected an AI-powered release notes summarisation solution integrating Azure OpenAI into Azure Pipelines, using system and user prompt engineering against a deployed LLM to auto-generate non-technical summaries for business and audit audiences.
Designed and maintained CI/CD pipelines in Azure DevOps for automated build, test and deployment across multiple environments.
Built self-service EIS deployment automation that dynamically fetches approvers, detects deployment conflicts and orchestrates sequential deployments — with real-time MS Teams notifications and near-zero wait time.
Implemented an Azure DevOps Boards ↔ ServiceNow integration to improve ticket traceability and reduce developer overhead.
Monitored production with Dynatrace, triaged ServiceNow incidents, and performed root cause analysis on performance issues.
Investigated and resolved AKS cluster incidents — health checks, pod log analysis, deployment troubleshooting.
Led the SonarQube upgrade to the 2025 LTA version across multiple application teams.

Azure DevOps (ADO)JenkinsGitHubGitLabGitNexusCD CDSonarQubeServiceNow IntegrationDockerKubernetesLinux Shell ScriptingAzure OpenAILLM IntegrationPrompt EngineeringAzure Logic AppsGenerative AI

Senior DevOps Engineer

Tata Consultancy Services · Client: Lloyds Banking Group PLC · London, UK · Jan 2022 – Dec 2024

In Simple Words

I worked across a central platform team supporting fifteen other teams' tooling, and found £6,500 a month in savings by shutting down infrastructure nobody was using anymore.

Technical Details

Collaborated with 15 platform teams, managing enterprise DevOps tooling: Git, GitHub, Jenkins, Docker, Kubernetes, Terraform, Rancher, Nexus, Dynatrace, Vault, and U-Deploy.
Optimised cloud infrastructure by decommissioning 53 inactive services, reducing server workload by 30% and delivering £6,500/month in cost savings.
Built Linux shell scripting automation to streamline repetitive operational tasks.
Used Dynatrace to monitor platform health, analyse performance metrics, and perform incident triage and root cause analysis.
Troubleshot Kubernetes cluster issues — container logs, deployment validation, pod failure resolution.
Spearheaded a Disaster Recovery solution for Nexus3, improving platform resilience.

CD CDJenkinsGitHubGitNexusSonarQubeServiceNow IntegrationDockerKubernetesLinux Shell Scripting

Python & PL/SQL Developer

Tata Consultancy Services · Client: Cigna Healthcare · Pune, India · Aug 2019 – Dec 2021

In Simple Words

My first role out of university — leading a small Scrum team to ship defect-free healthcare software, and automating a manual enrolment process with Python.

Technical Details

Delivered 30 defect-free modules across 6 sprints as Scrum Team Lead, coordinating with senior architects on sprint planning.
Developed an end-to-end ETL process in Python, automating member enrolment workflows and email notifications.
Led refactoring of UC4 scheduling tool modules to SDLC standards, deploying new modules via a DevOps pipeline.

PythonPL/SQLETLScrum

Business Impact

Real impact, measured in time saved, costs reduced, and teams empowered.

0%

Cut in daily manual release effort

4 hours → 1.5 hours, via full EIS build lifecycle automation.

£0

Infrastructure cost saved every month

From decommissioning 53 inactive services.

0%

Server workload reduction

Across a shared platform used by 15 teams.

0

Platform teams supported centrally

Enterprise-scale DevOps tooling at Lloyds Banking Group.

Technology Ecosystem

The stack, by what it's for — not an alphabetical wall of logos.

Cloud & Infrastructure

CI/CD & Delivery

Monitoring & Governance

Programming & AI

Hover or tap an icon for years of experience and how it's used day to day.

AI & Automation

Bridging Engineering and Business with AI

In Simple Words

I designed and implemented an LLM-powered release intelligence solution using Azure OpenAI. By combining Azure DevOps automation, API-driven data extraction, and prompt engineering, the system converts technical release information into structured, business-friendly summaries that improve communication across engineering, business, and audit teams.

Technical Details

Integrated Azure OpenAI into Azure Pipelines as a release-stage task.
Designed system and user prompts to constrain tone, length and audience (non-technical, business/audit-facing).
Output feeds directly into the existing EIS release workflow — no separate tool or manual step.
Applied the same prompt-engineering approach to day-to-day workflows using ChatGPT and GitHub Copilot.

Azure OpenAI · Release Summary

Pipeline log excerpt

Training & Certifications

Continuous learning, reinforced by both hands-on training and formal credentials.

Training

DEV

DevOps Engineer Training

Edureka

Completed

DevOps Engineer Training

Structured training covering CI/CD design, infrastructure automation, and release engineering.

Completed

K8S

Kubernetes Administrator (CKAD)

Edureka

Completed

Kubernetes Administrator (CKAD)

Application-focused Kubernetes training covering deployments, scaling, and troubleshooting.

Completed

ENG

Bachelor of Engineering

Amravati University

Graduated

Bachelor of Engineering

Foundational engineering degree completed from 2015 to 2019.

Graduated

Certifications

Microsoft AZ-900

Microsoft

Active

Microsoft AZ-900

Foundational knowledge of Azure cloud concepts, services, security, and pricing.

Current status: Active

Microsoft AZ-104

Microsoft

Renewal Needed

Microsoft AZ-104

Practical Azure administration skills for identity, networking, governance, and compute.

Current status: Renewal Needed

Microsoft AZ-400

Microsoft

Renewal Needed

Microsoft AZ-400

DevOps engineering expertise across CI/CD, automation, and delivery practices.

Current status: Renewal Needed

AWS Certified Cloud Practitioner

AWS

Active

AWS Certified Cloud Practitioner

Broad cloud fundamentals with an emphasis on AWS core services and adoption concepts.

Current status: Active

About Me

How I actually work.

I default to automating anything I do twice. If a task is manual, repeatable and boring, I treat that as an open bug — not a fact of life. That mindset is behind most of the numbers on this page.

Engineering Philosophy

If a deployment needs me personally to click "approve," that's a design flaw, not job security. I build self-service systems — like automated approver routing — so teams don't have to wait on one person to move forward.

Continuous Learning

Azure has been home for seven years, so I'm deliberately building outside it — hands-on AWS, deeper Kubernetes trainings, plus ongoing applied AI practice with more in depth learning.

Working Style

I treat incidents as mine to own until resolved — staying calm, communicating clearly, and pushing past the quick patch to find what actually broke.

Beyond Work

Structured early mornings, disciplined training, and a genuine interest in how far AI can push DevOps next.

Contact

Let's talk about your platform.

Whether it's a pipeline that needs to trust itself more, or a workflow that's ready for AI — I'm always happy to talk shop.

Email

amolsjadhav6213@gmail.com

Mobile

+44 7586 199755

LinkedIn linkedin.com/in/amol-s-jadhav

GitHub github.com/AmolJadhav97

Location Eastleigh, United Kingdom

Download Resume